[pc2g4d]

What's the multithreading story? tch-rs's (and libtorch's) lack of real threading support was causing problems for my async code - at least, I haven't found a way to work around it yet, given my level of rust knowledge.

Tangentially: I keep thinking an ML framework could be done based on Rust macros, so the automatic differentiation is done entirely at compile time. `let grad = autodiff!(x + y);` (The `autodiff` crate does this at runtime IIUC). Then the compiler's optimizations can apply to the static computation graph.

I always thought that was the vision for TF in the early days, but clearly it moved in a more dynamic direction under PyTorch's influence.

[l-m-z]

The tensors should be Send and Sync so can be manipulated from multiple threads, the underlying data is protected by a RWLock to guard against data races. The heavy operations such as matrix multiplication will be run on multiple cores even without using some explicit threading.